Introducing Kanon 2 Enricher — the world’s first hierarchical graphitization model

Kanon 2 Enricher, introduced as the first hierarchical graphitization model, transforms unstructured documents into structured knowledge graphs with high efficiency and sub-second latency. It outputs to the Isaacus Legal Graph Schema (ILGS), which is freely available for promoting open legal AI research. Unlike traditional extraction or generative models, Kanon 2 avoids generating hallucinations and excels in entity extraction, disambiguation, and hierarchical document segmentation. It has been tested through the Isaacus Beta Program and applied in diverse fields, including legal research and financial forensics, with notable use cases like creating knowledge graphs for regulatory analysis and enhancing contract ingestion pipelines. Kanon 2’s architecture allows it to efficiently handle large documents, outperforming leading language models by directly annotating documents rather than generating tokens sequentially. Future plans include the release of the Blackstone Graph, a comprehensive legal knowledge base, and the development of Kanon 3 Enricher and Kadi, an advanced legal reasoning model.